Optimal decarbonisation pathway for mining truck fleets

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dc.contributor.author Yu, Gang
dc.contributor.author Ye, Xianming
dc.contributor.author Ye, Yuxiang
dc.contributor.author Huang, Hongxu
dc.contributor.author Xia, Xiaohua
dc.date.accessioned 2025-03-20T11:56:06Z
dc.date.available 2025-03-20T11:56:06Z
dc.date.issued 2024-09
dc.description DATA AVAILABILITY : Data will be made available on request. en_US
dc.description.abstract The fossil fuel powered mining truck fleets can contribute up to 80% of total emissions in open pit mines. This study investigates the optimal decarbonisation pathway for mining truck fleets. Notably, our proposed pathway incorporates power generation, negative carbon technologies, and carbon trading. Technical, financial, and environmental models of decarbonisation technologies are established, capturing regional variations and time dynamic characteristics such as cost trends and carbon capture efficiency. The dynamic natures of characteristics pose challenges for using the cost-effective analyses approach to find the optimal decarbonisation pathway. To address this, we introduce a mixed-integer programming optimisation framework to find the decarbonisation pathway with minimum life cycle costs during the planning period. A case study for the optimal decarbonisation pathway of truck fleets in a South African coal mine is conducted to illustrate the applicability of the proposed model. Results indicate that the optimal decarbonisation pathway is significantly influenced by factors such as land cost, annual budget, and carbon trading prices. The proposed method provides invaluable guidance for transitioning towards a cleaner and more sustainable mining industry. en_US
dc.description.department Electrical, Electronic and Computer Engineering en_US
dc.description.librarian am2024 en_US
dc.description.sdg SDG-07:Affordable and clean energy en_US
dc.description.sdg SDG-09: Industry, innovation and infrastructure en_US
dc.description.sdg SDG-12:Responsible consumption and production en_US
dc.description.sponsorship National Key R&D Program of China, National Natural Science Foundation of China, National Research Foundation China/South Africa Research Cooperation Programme and Royal Academy of Engineering Transforming Systems through Partnership grant scheme. en_US
dc.description.uri www.keaipublishing.com/en/journals/journal-of-automation-and-intelligence/ en_US
dc.identifier.citation Yu, G., Ye, X., Ye, Y. et al. 2024, 'Optimal decarbonisation pathway for mining truck fleets', Journal of Automation and Intelligence, vol. 3, pp. 129-143. https://DOI.org/10.1016/j.jai.2024.03.003. en_US
dc.identifier.issn 2949-8554
dc.identifier.other 10.1016/j.jai.2024.03.003
dc.identifier.uri http://hdl.handle.net/2263/101628
dc.language.iso en en_US
dc.publisher KeAi Communications en_US
dc.rights © 2024 The Authors. This is an open access article under the CC BY-NC-ND license. en_US
dc.subject Coal mine en_US
dc.subject Truck fleet en_US
dc.subject Carbon emission en_US
dc.subject Optimal decarbonisation pathway en_US
dc.subject SDG-07: Affordable and clean energy en_US
dc.subject SDG-09: Industry, innovation and infrastructure en_US
dc.subject SDG-12: Responsible consumption and production en_US
dc.title Optimal decarbonisation pathway for mining truck fleets en_US
dc.type Article en_US


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